Lucky or good: 2012-2013 Historical Comparables

The New Jersey Devils were the poster child for bad luck last year. In spite of putting up a 55.6 CF% in close situations, the Devils couldn’t seem to get the puck into their opponents net or to keep it out of their own. Finishing with a 984 PDO, the Devils slid from Stanley Cup finalists to lottery picks, amassing only 48 points over the shortened season and finishing 11th in the East.

The Toronto Maple Leafs, on the other hand, seemed to have all the bounces go their way. The Leafs somehow managed to overcome a dreadful 43.6 CF% to make the playoffs for the first time since before the 04/05 lockout. Not only did Joffrey Lupul put up an otherworldly 18% even-strength on-ice shooting percentage, but James Reimer also emerged as the number one goaltender Buds fans had been waiting years for, posting a .924 even strength save percentage in 33 regular season games. The number that their detractors keyed in on though was their PDO (ok, everyone noticed the CF% too): at 1029, the Leafs couldn’t possibly sustain their position in the standings for very long, and were certainly due to come crashing back to Earth.

All over the shortened season, fans have bemoaned their team’s lack of luck, or cursed the favour the hockey gods seemed to have bestowed upon their rivals. A good question to ask though, is how much luck did the Leafs/Pens/Ducks/Insert Your Preferred Team Here actually get, and how much of their results should we have expected. While extreme PDO numbers are generally thought of as our best indicator of good or bad luck, there is at least some evidence that the two components of PDO (shooting and save percentage) are repeatable skills.

Even if we just suspect that PDO may be representative of skill rather than luck, we still have ways that we can look into how lucky or unlucky a particular team was given the stats they managed to post. One way of doing that is to look at which teams from the past that were similar to a given team, and then to compare the winning percentage that our 2012-2013 teams achieved with what their historical counterparts managed to post. Any teams that exceeded the winning percentage of their comparables can be considered relatively lucky, while those that underperformed are probably wishing that the season had been a full 82 games.

To figure out which teams were appropriate historical comparisons, I took all the team-level 5v5 Close data from the past 6 years from stats.hockeyanalysis.com and computed z-scores for each team’s CF20, CA20 and PDO. I then found each team’s 5 nearest neighbours using these metrics, and calculated a weighted average expected winning percentage and points percentage, the results of which are shown in the table below.

Team

Avg. Distance

Nearest Distance

Win%

Pts%

Neighbour Win%

Neighbour Pts. %

Win% Out(under) perform

Pts% Out(under) perform

Anaheim

0.620

0.498

62.50%

68.80%

50.26%

55.11%

12.24%

13.69%

Boston

1.000

0.657

58.33%

64.60%

59.25%

63.83%

-0.91%

0.77%

Buffalo

0.627

0.280

43.75%

50.00%

52.93%

56.28%

-9.18%

-6.28%

Calgary

0.957

0.636

39.58%

43.80%

39.66%

44.02%

-0.08%

-0.22%

Carolina

1.252

0.714

39.58%

43.80%

44.55%

50.49%

-4.96%

-6.69%

Chicago

1.074

0.847

75.00%

80.20%

54.64%

59.80%

20.36%

20.40%

Colorado

0.851

0.459

33.33%

40.60%

38.56%

42.82%

-5.23%

-2.22%

Columbus

0.686

0.540

50.00%

57.30%

53.06%

57.54%

-3.06%

-0.24%

Dallas

0.734

0.606

45.83%

50.00%

51.94%

58.02%

-6.10%

-8.02%

Detroit

0.657

0.580

50.00%

58.30%

50.14%

55.60%

-0.14%

2.70%

Edmonton

0.544

0.255

39.58%

46.90%

43.21%

47.78%

-3.63%

-0.88%

Florida

2.455

2.178

31.25%

37.50%

42.50%

46.14%

-11.25%

-8.64%

L.A.

0.704

0.325

56.25%

61.50%

59.07%

64.08%

-2.82%

-2.58%

Minnesota

0.538

0.435

54.17%

57.30%

40.37%

46.11%

13.80%

11.19%

Montreal

0.474

0.369

60.42%

65.60%

54.77%

59.47%

5.65%

6.13%

Nashville

0.989

0.758

33.33%

42.70%

44.56%

49.39%

-11.23%

-6.69%

New Jersey

1.144

0.819

39.58%

50.00%

50.60%

55.06%

-11.01%

-5.06%

NY Islanders

0.400

0.309

50.00%

57.30%

49.94%

54.44%

0.06%

2.86%

NY Rangers

0.595

0.224

54.17%

58.30%

51.61%

55.90%

2.56%

2.40%

Ottawa

0.483

0.355

52.08%

58.30%

54.78%

59.04%

-2.69%

-0.74%

Philadelphia

0.402

0.203

47.92%

51.00%

43.86%

49.51%

4.06%

1.49%

Phoenix

0.337

0.211

43.75%

53.10%

51.86%

57.81%

-8.11%

-4.71%

Pittsburgh

1.271

0.837

75.00%

75.00%

57.63%

63.33%

17.37%

11.67%

San Jose

0.460

0.235

52.08%

59.40%

54.79%

59.29%

-2.70%

0.11%

St. Louis

0.738

0.627

60.42%

62.50%

44.16%

49.68%

16.25%

12.82%

Tampa Bay

0.644

0.553

37.50%

41.70%

38.46%

42.87%

-0.96%

-1.17%

Toronto

1.707

1.637

54.17%

59.40%

43.71%

49.76%

10.45%

9.64%

Vancouver

0.698

0.254

54.17%

61.50%

58.32%

61.73%

-4.15%

-0.23%

Washington

0.556

0.473

56.25%

59.40%

46.45%

52.40%

9.80%

7.00%

Winnipeg

0.821

0.564

50.00%

53.10%

50.58%

56.55%

-0.58%

-3.45%

The first thing to notice is that the shortened season does seem to have had quite a large effect on the standings, with many teams finishing far away from their expected level given their historical comparables. Looking at the table, we see that the results range from underperforming by 11.25% (Florida) to overperforming by 20.36% (Chicago). This isn’t to say that Chicago was necessarily a bad team (or that Florida was a good team by any means), but rather that we’d expect a team who generated roughly as many Corsi events for and against as Chicago, and whose PDO was in a similar range to win only about 54.6% of their games, rather than the 75% the Blackhawks managed to achieve last year. To contrast this with 2011-2012, the range of under/outperform was between 6.46% underperform to 1.44% overperform, which suggests that 48 games doesn’t seem to be enough time for the randomness of hockey to sort itself out fully, and for most teams to reach their true talent winning percentage.

But back to where we started: the Leafs and the Devils. Looking at the data, we can see that New Jersey definitely does have reason to claim that fortune wasn’t on their side. Lou Lamoriello’s club underperformed their expected winning percentage by 11%, good for the 3rd worst underperform of any team, and the 7th furthest in absolute terms from their expected winning percentage. It’s interesting to see that the Devils did appear to do decently enough in terms of points percentage: their 5.04% underperform was roughly in the middle of the pack for teams in the league this year.

On the other hand, while the Leafs also finished far from where their historical peers would have suggested, they were definitely not the luckiest team in the league last season. At 10.5% above their expected winning percentage (and 9.4% above their expected points percentage), the Leafs were still behind Chicago, Pittsburgh, Anaheim, St. Louis and Minnesota in terms of outperformers. What might be most important to note though is how different the Leafs were from all the teams in our historical set. The Leafs had the 2nd farthest nearest neighbour and 2nd largest average neighbour distance of all the clubs from last year. What this means is we can’t necessarily trust our prediction of the Leafs expected winning percentage as much as we’d like, given how few similar teams we’ve seen over the last 6 years. This may also give us some hints as to how Toronto managed to do so well when their closest comparables have tended to fail pretty miserably.

A few stray observations:

Moreso than the Leafs, Florida was a really unique team last year. The Panthers were the furthest from any team in the past 6 years, driven mostly by their unbelievably terrible PDO. The Panthers combined shooting and save percentage was a dreadful 951, 23 points below their closest neighbour. Even if we were optimistic and brought them up to the same level as their neighbours, their 46.4% points percentage would have had them in the bottom 6 in the league.

While the Blackhawks and Penguins certainly had good seasons, looking at their expected winning percentages it becomes clear that it’s unlikely they would have been able to keep up their pace over the course of a full season. In the salary-cap era NHL it’s simply too difficult for a team to earn more than 75% of their possible points.

Team to watch out for this year (excl. NJ): Phoenix. The Coyotes actually had the lowest average distance of all teams last year (meaning we have a pretty good estimate of how they should have done), and their comparables were very favourable: if they’d won at the same rate as the teams most similar to them statistically, they would have just edged out Minnesota for the last playoff spot in the West.

Team who may be in for a rude awakening this year (excl. Toronto): St. Louis. I’m really pulling for Brian Elliott and co. to keep things together, but the numbers don’t seem to support their ability to do so. Their closest comparables posted a sub-.500 average record, and given Elliott’s track history you have to wonder how long he can keep up his world-beating play.